Title :
Indexing melodic sequences via Wavelet transform
Author_Institution :
Dipt. di Inf. e Comun., Univ. degli Studi di Milano, Milan, Italy
fDate :
June 28 2009-July 3 2009
Abstract :
Wavelet decomposition has been widely used in video and audio signal analysis. Here we propose a wavelet based method for indexing symbolic music material which is based on the Haar transform. Melodies are represented by pitch-class sequences at different levels of resolution. We show that it is possible to efficiently index long melodic sequences by means of their Haar transform at different levels without losing musical information. We present an experimental evaluation of this approach based on a subset of the RISM collection consisting in about 500 monophonic incipits. Results have been evaluated against a ground truth for the same collection for queries with diverse characteristics.
Keywords :
Haar transforms; acoustic signal processing; indexing; music; signal resolution; wavelet transforms; Haar transform; audio signal analysis; melodic sequence indexing; pitch-class sequences; symbolic music indexing; video signal analysis; wavelet decomposition; wavelet transform; Extraterrestrial measurements; Fluctuations; Frequency; Indexing; Multimedia databases; Music information retrieval; Signal analysis; Signal resolution; Wavelet analysis; Wavelet transforms; content description; indexing; multimedia databases; music; retrieval;
Conference_Titel :
Multimedia and Expo, 2009. ICME 2009. IEEE International Conference on
Conference_Location :
New York, NY
Print_ISBN :
978-1-4244-4290-4
Electronic_ISBN :
1945-7871
DOI :
10.1109/ICME.2009.5202636